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We’re pleased to announce d3heatmap, our new package for generating interactive heat maps using d3.js and htmlwidgets. Tal Galili, author of dendextend, collaborated with us on this package. d3heatmap is designed to have a familiar feature set and API for anyone who has used heatmap or heatmap.2 to create static heatmaps. You can specify dendrogram, clustering, and scaling options

Previously I shared the data visualization approach for descriptive analysis of progress of cohorts with the “layer-cake” chart (part I and part II). In this post, I want to share another interesting visualization that not only can be used for descriptive analysis as well but would be more helpful for analyzing a large number of cohorts.... Read More »

At our most recent R user group meeting we were delighted to have presentations from Mark Lawson and Steve Hoang, both bioinformaticians at Hemoshear. All of the code used in both demos is in our Meetup’s GitHub repo.Making heatmaps in RSteve started with an overview of making heatmaps in R. Using the iris dataset, Steve demonstrated...

In February the WSJ graphics team put together a series of interactive visualisations on the impact of vaccination that blew up on twitter and facebook, and were roundly lauded as great-looking and effective dataviz. Some of these had enough data available to look … Continue reading →

Inspired by this tweet, I wanted to try to do something similar in JavaScript. Very cool hack: Extracting the original data from a heatmap image with R vector ops #rstats http://t.co/Lbi6FCXdrI pic.twitter.com/LCabkMGjXY— Gregory Piatetsky (@kdnugge...

The paper Analysis of the Linux Kernel Evolution Using Code Clone Coverage analysed 136 versions of Linux (from 1.0 to 2.6.18.3) and calculated the amount of source code that was shared, going forward, between each pair of these versions. When I saw the heatmap at the end of the paper (see below) I knew it

Several months ago, I found Bryan Povlinkski's (really nicely cleaned) dataset with 2013 NFL play-by-play information, based on data released by Brian Burke at Advanced Football Analytics. I decided to browse QB completion rates based on Pass Location (Left, Middle, Right), Pass Distance (Short or Deep), and Down....

UPDATE The statebins package is now available on CRAN
I became enamored (OK, obsessed) with a recent visualization by the WaPo team which @ryanpitts tweeted and dubbed statebins:
Statebins! RT @kevinschaul: States with the most jobs lost or threatened because of trade. http://t.co/r1pJhudpz3 pic.twitter.com/eMozAgyEAb— Ryan Pitts (@ryanpitts) August 24, 2014
In a very real sense...

A little while back there was an article in blogTO about how a reddit user had used data from Toronto's Open Data initiative to produce a rather cool-looking map of all the locations of all the traffic signals here in the city.It's neat because as the author on blogTO notes, it is recognizable as Toronto...

Apparently, this turned out to be my most popular post ever. Of course there are lots of things to say about the heatmap (or quilt, tile, guilt plot etc), but what I wrote was literally just a quick celebratory post to commemorate that I’d finally grasped how to combine reshape2 and ggplot2 to quickly make